The filmed presentations of the project conference are now available on YouTube, the links can be found here. Thanks go to Doug Rocks-Macqueen (Landward Research) for the video registration and presentation.

On 27 June 2016 we organized a one-day seminar at VU University on the theme ‘Detection and Modelling of Ancient Pathways’. Computer-based modelling of movement and transport in prehistory, and the detection and interpretation of ancient pathways from LiDAR images have both attracted much interest in the community of ‘digital archaeology’. Up to now, however, there have been few attempts to link pathway modelling to detection and vice versa. Experts from France, Slovenia, the United States and the Netherlands presented the state of the art in both fields, and explored the possible connections between the two.

The seminar was co-sponsored by CLUE+, VU’s Research Institute for Culture, History and Heritage, and ARCHON, the Dutch Research School of Archaeology.

Our second project paper was published today, on testing the robustness of local network metrics. It was published in Frontiers in Digital Humanities, a new Open Access journal that we can recommend for the efficiency of its reviewing and publishing procedures. We would also like to thank Dr. Tom Brughmans, the editor of the special issue on ‘Network Science Approaches for the Study of Past Long-Term Social Processes’ for inviting us to submit.

The ‘Roman farming’ simulation model is now close to completion. Jamie Joyce has presented preliminary results of the model runs at the TRAC2016 conference in Rome, and at CAA2016 in Oslo. Mark Groenhuijzen has presented a further analysis of the robustness of network measures at CAA2016, and a paper on the subject is in preparation. We found the debate on modelling at CAA2016 particularly stimulating and encouraging, and we would like to thank the CAA Special Interest Group on Complex Systems Simulation for organizing the round table in which we participated.

Earlier this year, the palaeogeographic reconstruction of the Limes area for the Roman period was completed. We are now using this data to run site location analyses, which will provide input for the simulation models in order to better estimate the agricultural potential and carrying capacity of the region.

We have also started a collaboration with VU’s SpInLab (Maurice de Kleijn MA and Frank Beijaard MA), within the framework of the EU-funded HERCULES project. Within this project, a pilot study is run to see whether a modern land use forecasting tool, the Land Use Scanner, can be applied to ‘retrodict’ land allocation processes in the past. This tool has clear advantages over using agent-based modelling, since it is capable of dealing with larger spatial datasets in a very efficient way. However, it needs to be adapted to historical scenarios and confronted with archaeological datasets to see whether it also works for predicting the past. The Dutch Limes is one of the cases studied, and we expect the outcomes of this experiment to provide us with more insight in the spatio-temporal development of land use in the Roman period.

The project is now getting on its way to completion, and preliminary results will be made available over the next few months. Two more papers submitted to the LAC2014 conference proceedings on modelling animal husbandry and demography are scheduled to be published in April 2016. For now, we want to draw your attention to an overview lecture given by Philip Verhagen on Nov 10, and to the presentation given by Mark Groenhuijzen at the CAA-NL/FL conference on Oct 22 in Amsterdam on simulating local transport networks. We will also present the first results of the project for a Dutch audience at the Romeinensymposium on Dec 18 in Amsterdam.

The archaeological database is now completed. All in all, we have identified and checked more than 1500 Roman sites, of which some 1300 will be retained for site location analysis. We intend to publish a paper on the issue of database uncertainty in the course of 2016, and are looking into options of making the data publicly available after completion of the project.